Explore the key aspects of building an interpretable AI model using a glass box approach. The post explains deep learning, the issue of model interpretability, and provides a step-by-step Python code example using Explainable Boosting Machine to predict breast cancer. Glass box models versus black box models, and key features for breast cancer detection are discussed.
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Artificial Intelligence and the Rise of Deep LearningA Big Problem in Deep Learning: Lack of InterpretabilityA Solution to Interpretability: Glass Box ModelsCode Example: Solving the Problem with Explainable AIConclusion: KAN (Kolmogorov–Arnold Networks)1 Comment
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